Molecular analysis of the bacterial microbiota in the human stomach
Bibliographic record
Abstract
The microbiota of the human stomach and the influence of Helicobacter pylori colonization on its composition remain largely unknown. We characterized bacterial diversity within the human gastric mucosa by using a small subunit 16S rDNA clone library approach and analyzed 1,833 sequences generated by broad-range bacterial PCR from 23 gastric endoscopic biopsy samples. A diverse community of 128 phylotypes was identified, featuring diversity at this site greater than previously described. The majority of sequences were assigned to the Proteobacteria, Firmicutes, Actinobacteria, Bacteroidetes, and Fusobacteria phyla. Ten percent of the phylotypes were previously uncharacterized, including a Deinococcus-related organism, relatives of which have been found in extreme environments but not reported before in humans. The gastric clone libraries from 19 subjects contained H. pylori rDNA; however, only 12 of these subjects tested positive for H. pylori by conventional laboratory methods. Statistical analysis revealed a large degree of intersubject variability of the gastric ecosystem. The presence of H. pylori did not affect the composition of the gastric community. This gastric bacterial rDNA data set was significantly different from sequence collections of the human mouth and esophagus described in other studies, indicating that the human stomach may be home to a distinct microbial eco-system. The gastric microbiota may play important, as-yet-undiscovered roles in human health and disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".